Wireless integrated network sensors
Communications of the ACM
System architecture directions for networked sensors
ASPLOS IX Proceedings of the ninth international conference on Architectural support for programming languages and operating systems
Contiki - A Lightweight and Flexible Operating System for Tiny Networked Sensors
LCN '04 Proceedings of the 29th Annual IEEE International Conference on Local Computer Networks
TinyDB: an acquisitional query processing system for sensor networks
ACM Transactions on Database Systems (TODS) - Special Issue: SIGMOD/PODS 2003
Protocols and Architectures for Wireless Sensor Networks
Protocols and Architectures for Wireless Sensor Networks
Avrora: scalable sensor network simulation with precise timing
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
Validated cost models for sensor network queries
Proceedings of the Sixth International Workshop on Data Management for Sensor Networks
SmartCIS: integrating digital and physical environments
ACM SIGMOD Record
SNEE: a query processor for wireless sensor networks
Distributed and Parallel Databases
Distributed and Parallel Databases
Resilient sensor network query processing using logical overlays
MobiDE '12 Proceedings of the Eleventh ACM International Workshop on Data Engineering for Wireless and Mobile Access
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The typical nodes used in mote-level wireless sensor networks (WSNs) are often brittle and severely resource-constrained. In particular, nodes are often battery-powered, thereby making energy depletion a significant risk. When changes to the connectivity graph occur as a result of node failure, the overall computation may collapse unless it is capable of adapting to the new WSN state. Sensor network query processors (SNQPs) construe a WSN as a distributed, continuous query platform where the streams of sensed values constitute the logical extents of interest. Crucially, in the context of this paper, they must make assumptions about the connectivity graph of the WSN at compile time that are likely not to hold for the lifetime of the compiled query evaluation plans (QEPs) the SNQPs generate. This paper address the problem of ensuring that a QEP continues to execute even if some nodes fail. The goal is to extend the lifetime of the QEP, i.e., the period during which it produces results, beyond the point where node failures start to occur. We contribute descriptions of two different approaches that have been implemented in an existing SNQP and present experimental results indicating that each significantly increases the overall lifetime of a query compared with non adaptive approach.